Oral microflora in children with hematologic malignancies
https://doi.org/10.17650/1818-8346-2015-10-2-51-57
Abstract
The goal was a comprehensive study of oral microflora in healthy children and those with hematologic malignancies, based on the analysis of mixed microbial biofilms composition, isolation and identification of new previously unknown microorganisms. The material was obtained in children with hematological diseases in remission, 2–10 years aged, and for the control group from St. Petersburg schoolchildren and in kindergartens. We used microbiological, biochemical and molecular genetic methods, including electron microscopy, proteomic analysis, sequencing and complete genome annotation. Microorganisms of 23 genera isolated as pure cultures and identified by biochemical activity from mixed microbial biofilm derived from saliva of healthy and sick children. In microflora of children with hematologic malignancies a previously unknown type of streptococci with a large number of antibiotic resistance genes was revealed. Differences in oral microbiota composition of healthy children and children with hematological diseases in remission were revealed. The microbiota of children with hematologic malignancies contains more genes controlling antibiotic resistance. Also, it was observed previously unknown bacterium of the genus Streptococcus.
About the Authors
M. F. Vecherkovskaya
Acad. I.P. Pavlov First St. Petersburg State Medical University, Ministry of Health of Russia; 6–8 L, va Tolstogo St., St. Petersburg, 197022, Russia
Russian Federation
Russian Federation
G. V. Tets
Acad. I.P. Pavlov First St. Petersburg State Medical University, Ministry of Health of Russia; 6–8 L, va Tolstogo St., St. Petersburg, 197022, Russia
Russian Federation
Russian Federation
B. V. Afanasiev
Acad. I.P. Pavlov First St. Petersburg State Medical University, Ministry of Health of Russia; 6–8 L, va Tolstogo St., St. Petersburg, 197022, Russia
Russian Federation
Russian Federation
V. V. Tets
Acad. I.P. Pavlov First St. Petersburg State Medical University, Ministry of Health of Russia; 6–8 L, va Tolstogo St., St. Petersburg, 197022, Russia
Russian Federation
Russian Federation
References
1. Sommer F., Bäckhed F. The gut microbiota – masters of host development and physiology. Nat Rev Microbiol 2013;11:227–38.
2. Epstein S. Microbiology monographs. Springer Berlin Heidelberg, 2009. Pp. 10, 131–159.
3. Zaura E., Keijser B. J.F., Huse S. M., Crielaard W. Defining the healthy “core microbiome” of oral microbial communities. BMC Microbiol 2009;9:259.
4. David B., Richard C. Bergey, s Manual of Systematic Bacteriology. Vol. 1–5. Springer, 2012.
5. Altschul S. F., Gish W., Miller W. et al. Basic local alignment search tool. J Mol Biol 1990;215:403–10.
6. Larkin M. A., Blackshields G., Brown N. P. et al. Clustal W and Clustal X version 2.0. Bioinformatics 2007;23:2947–4.
7. Миллер Д. Эксперименты в молекулярной генетике. М.: Мир, 1976. 440 с. [Miller D. Experiments in molecular genetics. M.: Mir, 1976. 440 p. (In Russ.)].
8. Frank J. A., Reich C. I., Sharma S. et al. Critical evaluation of two primers commonly used for amplification of bacterial 16S rRNA genes. Appl Environ Microbiol 2008;74:2461–70.
9. Wright E. S., Yilmaz L. S., Noguera D. R. DECIPHER, a search-based approach to chimera identification for 16S rRNA sequences. Appl Environ Microbiol 2012;78:717–25.
10. Edgar R. C., Haas B. J., Clemente J. C. et al. UCHIME improves sensitivity and speed of chimera detection. Bioinformatics 2011;27:2194–200.
11. Wiley E. O., Lieberman B. S. Phylogenetics: theory and practice of phylogenetic systematics. John Wiley & Sons Inc., 2011.Available at http://www.wiley.com.
12. Ludwig W., Strunk O., Westram R. et al. ARB: a software environment for sequence data. Nucleic Acids Res 2004:32:1363–71.
13. Guindon S., Dufayard J. F., Lefort V. et al. New algorithms and methods to estimate maximum-likelihood phylogenies: assessing the performance of PhyML 3.0. Syst Biol 2010;59:307–21.
14. Zerbino D. R. Using the Velvet de novo assembler for short-read sequencing technologies. Curr Protoc Bioinformatics 2010; chapter 11, unit 11.5.
15. Darling A. E., Mau B., Perna N. T. ProgressiveMauve: multiple genome alignment with gene gain, loss and rearrangement. PLoS ONE 2010;5:e11147.
16. Aziz R. K., Bartels D., Best A. A. et al. The RAST Server: rapid annotations using subsystems technology. BMC Genomics 2008;9:75.
17. Besemer J., Lomsadze A., Borodovsky M. GeneMarkS: a self-training method for prediction of gene starts in microbial genomes. Implications for finding sequence motifs in regulatory regions. Nucleic Acids Res 2001;29:2607–18.
18. Nawrocki E. P., Eddy S. R. Infernal 1.1: 100-fold faster RNA homology searches. Bioinformatics 2013;29:2933–5.
19. Burge S. W., Daub J., Eberhardt R. et al. Rfam 11.0: 10 years of RNA families. Nucleic Acids Res 2013;41: D226–32.
20. Finn R. D., Bateman A., Clements J. et al. Pfam: the protein families database. Nucleic Acids Res 2014;42:D222–30.
21. UniProt Consortium. Activities at the Universal Protein Resource (UniProt). Nucleic Acids Res 2014;42:D191–8.
22. Eaton J. W., Bateman D., Hauberg S. A high-level interactive language for numerical computations (gnu.org, 2011).
23. Tetz V. V. Colony-like communities of bacteria. Microbios 1994;80:63–5.
24. Tetz V. V. Formation and structure of mixed bacterial communities. APMIS 1999;107:645–54.
25. Morales D. K., Hogan D. A. Candida albicans interactions with bacteria in the context of human health and disease. PLoS Pathog 2010;6:e1000886.
26. Molin S., Tolker-Nielsen T. Gene transfer occurs with enhanced efficiency in biofilms and induces enhanced stabilisation of the biofilm structure. Curr Opin Biotechnol 2003;14:255–61.
27. Reichmann P., Nuhn M., Denapaite D. et al. Genome of Streptococcus oralis strain Uo5. J Bacteriol 2011;193: 2888–9.
28. Denapaite D., Brückner R., Nuhn M. et al. The genome of Streptococcus mitis B6 – what is a commensal? PLoS One 2010;5:e9426.
29. Hoskins J., Alborn W. E. Jr, Arnold J. et al. Genome of the bacterium Streptococcus pneumoniae strain R6. J Bacteriol 2001;183:5709–17.
30. Shahinas D., Tamber G. S., Arya G. et al. Whole-genome sequence of Streptococcus pseudopneumoniae isolate IS7493. J Bacteriol 2011;193:6102–3.
31. Chen T., Yu W. H., Izard J. et al. The Human Oral Microbiome Database: a web accessible resource for investigating oral microbe taxonomic and genomic information. Database (Oxford), 2010; baq013.
32. Schmitt B. H., Cunningham S. A., Dailey A. L. et al. Identification of anaerobic bacteria by Bruker Biotyper matrix-assisted laser desorption ionization-time of flight mass spectrometry with on-plate formic acid preparation. J Clin Microbiol 2013;51:782–6.
33. Bergey, s Manual of Systematic Bacteriology. Vol. 3: The Firmicutes. Springer, 2009.
Review
For citations:
Vecherkovskaya M.F., Tets G.V., Afanasiev B.V., Tets V.V. Oral microflora in children with hematologic malignancies. Oncohematology. 2015;10(2):51-57. (In Russ.) https://doi.org/10.17650/1818-8346-2015-10-2-51-57
Views:
10071
Email this article 